docs: def downsample_completeness_table(comp_table, sample_width=0.1, mmax=None):
      """
      Re-sample the completeness table to a specified sample_width
      """
      new_comp_table = []
      for i in range(comp_table.shape[0] - 1):
          mvals = np.arange(comp_table[i, 1],
                            comp_table[i + 1, 1], d_m)  # FIXME: d_m is undefined!
          new_comp_table.extend([[comp_table[i, 0], mval] for mval in mvals])
      # If mmax > last magnitude in completeness table
      if mmax and (mmax > comp_table[-1, 1]):
          new_comp_table.extend(
              [[comp_table[-1, 0], mval]
               for mval in np.arange(comp_table[-1, 1], mmax + d_m, d_m)])
      return np.array(new_comp_table)